Expansion of Medicaid managed care (MMC), a decline in Medicaid enrollment, and an increase in the number of uninsured children appears to be threatening the stability of pediatric safety net hospitals and Federally Qualified Health Centers (FQHC). Implementation of the State Children's Health Insurance Program (S-CHIP) may play a key role in their survival. The impact of these health care-related changes on community safety nets for children has not been studied. SPECIFIC AIMS The study will (1)describe relationship between characteristics of publicly funded programs and survival/financial viability of pediatric safety net providers (PSNP), (2) determine differential effects of MMC and S-CHIP for PSNPs relative to pediatric FQHCs, (3) investigate institutional and organizational factors among PSNPs that are precipitating change as a result of evolving Medicaid and S-CHIP programs, and (4)examine how successes and failures that PSNPs have experienced in confronting changes have affected their communities. STUDY DESIGN The unit of analysis is the individual pediatric safety net institution and the study period is 1996 through 1999. Safety net hospitals will be identified from the American Hospital Association's (AHA) Annual Survey of Hospitals and the Medicare Cost Report. FQHCs will be identified from the Uniform Data System (UDS). All hospitals with a high burden of uncompensated care (UC) and/or a large proportion of Medicaid revenues and all FQHCs will be included. Pediatric safety net hospitals and FQHCs will be selected by service mix (AHA data) and telephone survey to gather pediatric UC and Medicaid revenues for each hospital and by service mix and patient characteristics on the UDS, respectively. Key informant interviews will be conducted in MSAs with significant changes MMC and S-CHIP and in MSAs with significant negative, positive, or no changes in financial status of pediatric safety nets. Five case studies of MSAs with substantial change in MMC and S-CHIP and financial safety net success or failure will be conducted. ANALYSIS A logistic regression model will estimate the impact of hospital, market, and policy factors on closure. The model will indicate the extent to which baseline factors as well as changes in state Medicaid and S-CHIP policies affected the probability of closure over time. The hospital's cost, revenue, and profit equations will be modeled using a fixed effects regression model.